Blood lipid levels mediating the effects of sex hormone-binding globulin on coronary heart disease: Mendelian randomization and mediation analysis

Observational studies indicate that serum sex hormone-binding globulin (SHBG) levels are inversely correlated with blood lipid levels and coronary heart disease (CHD) risk. Given that dyslipidemia is an established risk factor for CHD, we aim to employ Mendelian randomization (MR) in conjunction with mediation analysis to confirm the mediating role of blood lipid levels in the association between SHBG and CHD. First, we assessed the causality between serum SHBG levels and five cardiovascular diseases using univariable MR. The results revealed causality between SHBG levels and reduced risk of CHD, myocardial infarction, as well as hypertension. Specifically, the most significant reduction was observed in CHD risk, with an odds ratio of 0.73 (95% CI 0.63–0.86) for each one-standard-deviation increase in SHBG. The summary-level data of serum SHBG levels and CHD are derived from a sex-specific genome-wide association study (GWAS) conducted by UK Biobank (sample size = 368,929) and a large-scale GWAS meta-analysis (60,801 cases and 123,504 controls), respectively. Subsequently, we further investigated the mediating role of blood lipid level in the association between SHBG and CHD. Mediation analysis clarified the mediation proportions for four mediators: high cholesterol (48%), very low-density lipoprotein cholesterol (25.1%), low-density lipoprotein cholesterol (18.5%), and triglycerides (44.3%). Summary-level data for each mediator were sourced from the UK Biobank and publicly available GWAS. The above results confirm negative causality between serum SHBG levels and the risk of CHD, myocardial infarction, and hypertension, with the causal effect on reducing CHD risk largely mediated by the improvement of blood lipid profiles.


Table S1-S4
Text S1 e Provide details of ethics committee approval and participant informed consent, if relevant.

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5 Assumptions Explicitly state the 3 core instrumental variable (IV) assumptions for the main analysis (relevance, independence, and exclusion restriction), as well assumptions for any additional or sensitivity analysis.Table S3, S4 c If the data sources include meta-analyses of previous studies, provide the assessments of heterogeneity acrossthese studies.

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the eligibility criteria and the sources and methods of selection of participants.Report the sample size and whether any power or sample size calculations were carried out prior to the main analysis.Describe measurement, quality control, and selection of genetic variants.Page 6 For each exposure, outcome, and other relevant variables, describe methods of assessment and diagnostic criteria for diseases.

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variants were handled in the analyses and, if applicable, how their weights were selected.estimator (eg, 2-stage least squares, Wald ratio) and related statistics.Detail the included covariates and, in case of 2-sample MR, whether the same covariate set was used for adjustment in the 2 samples.or prior knowledge used to assess the assumptions or justify their validity.analyses or additional analyses performed (eg, comparison of effect estimates from different approaches, independent replication, bias analytic techniques, validation of instruments, simulations).and package(s), including version and settings used.Page 8 State whether the study protocol and details were preregistered (as well as when and where). of individuals at each stage of included studies and reasons for exclusion.Consider use of a flow diagram.for phenotypic exposure(s), outcome(s), and other relevant variables (eg, means, SDs, proportions).

Supplementary Table S2. Detailed information on GWAS summary-level data of the dichotomous phenotypes
GWAS, genome-wide association study; AF&FL, atrial fibrillation & flutter; MRC-IEU, Medical Research Council Integrative Epidemiology Unit (University of Bristol); SNPs, single nucleotide polymorphisms.*Year of publication.Supplementary TableS3.

Characteristics of GWAS summary-level data for continuous phenotypes
* The

effect size is reported in standard deviation (SD) change, units in parentheses represents the original measurement of the biomarker level.
† VLDL-C

Table 2 Table S27 d
When relevant, report and compare with estimates from non-MR analyses.
N/A eConsider additional plots to visualize results (eg, leave-one-out analyses).